摘要
提出了一种基于模糊决策属性依赖度的属性相对约简算法。该算法利用粗糙集理论分析的方法,通过在知识表达系统中引入模糊决策属性依赖度的概念,来描述由条件属性所提供的知识对整体决策的依赖程度,并通过模糊决策属性依赖度定义了条件属性对模糊决策属性的相对重要性,以此作为启发式信息,可以方便地求出相对核,再以相对核作为求解最小相对约简的起点。按重要性的不同逐次选择重要属性添加到相对核中,直至其依赖度达到整体条件属性依赖度时为止。
A kind of attribute relative reduction for fuzzy decision attribute dependent degree is proposed.With rough set theory and fuzzy decision attribute dependent degree applied in knowledge express system,the dependent degree of the knowledge supplied by condition attribute for the whole decision is described and relative importance degree and relative core is obtained. Based on relative core,attributes are selected one by one and inserted into relative core according to their importance degree until the whole condition attribute dependent degree is met.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第28期151-153,共3页
Computer Engineering and Applications
基金
国家自然科学基金委员会与中国民用航空总局联合资助项目(No60672178)
中国民航大学博士启动基金资助项目(No05qd02s)
关键词
模糊粗糙集
知识表达系统
模糊决策属性依赖度
相对约简
fuzzy rough set
knowledge express system
fuzzy decision attribute dependent degree
relative reduction
